CV/ML Platform Engineer: GPU Kubernetes & Edge Deploy

Allen Control Systems; Austin (TX); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Paid Time Off

Job summary

A leading defense technology firm in Austin, Texas is seeking an experienced CV/ML Platform Engineer to design and manage essential infrastructure for the CV/ML team. You will deploy Kubernetes clusters and manage NVIDIA GPU infrastructure while automating ML processes and collaborating across teams. Ideal candidates should have a strong background in Platform Engineering or DevOps/MLOps, along with proven experience in GPU management and CI/CD pipelines. The role offers an exciting opportunity to work in a dynamic environment focused on advanced robotics and software.

Qualifications

• 2+ years of experience in Platform Engineering or DevOps/MLOps.
• Strong programming skills for automating ML lifecycles.
• Hands-on experience with NVIDIA GPU infrastructure.
• Experience implementing and maintaining MLOps platforms.
• Familiarity with high-performance storage solutions.
• Proven track record building CI/CD pipelines.
• Experience with model optimization toolchains.
• Proficiency with observability stacks.
• Strong Linux systems knowledge.

Responsibilities

• Deploy and operate Kubernetes clusters on bare-metal infrastructure.
• Manage NVIDIA GPU clusters for ML training.
• Own the ACS CV/ML CI/CD pipeline.
• Improve and maintain core ML infrastructure.
• Automate repetitive model training and testing tasks.
• Work with Software Team Platform Engineers for coordination.
• Collaborate with the Software Team on model optimization.

Job description

Allen Control Systems (ACS) is acutting-edgedefense startup founded by two former Navy electrical engineers with a proventrack recordin robotics and software. We are developing a small, autonomous gun turret that employs advanced computer vision and control systems to precisely target and neutralize small drones and loitering munitions. Our innovative approach requires overcoming significant technical challenges, making this an exciting and dynamic environment for experienced engineers.

With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders’ successful exits from twopreviousventuresacquiredfor a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop have a real-world impact.

Position Overview

We are seeking an experienced CV/ML Platform Engineer with specialization in Computer Vision and Machine Learning (CV/ML) to design, build, and own the data, model, and compute infrastructure powering ACS CV/ML team. You will help manage a 130+ GPU bare-metal Kubernetes cluster, own CV/ML CI/CD pipelines, and ensure ML model training proceeds at high volume with low friction.

What You'll Do:

• Deploy andoperateKubernetes clusters on bare-metal infrastructure hosting 130+ NVIDIA GPUs, with hybrid burst capability to AWS for scalable compute and storage workloads.
• Manage NVIDIA GPU clusters for ML training.
• Own the ACS CV/ML CI/CD pipeline.
• Improve and maintain core ML infrastructure, such as model registration and versioning, experiment tracking, and model and data provenance tracking.
• Improve and maintain ML model testing, performance analysis, and reporting tools.
• Automate repetitive model training and testing tasks to increase developer velocity.
• Work with Software Team Platform Engineers to ensure efficient coordination and minimal duplication between CV/ML infrastructure and wider Software infrastructure.
• Collaborate with the Software Team to automate the optimization of models (TensorRT/quantization) for deployment on NVIDIA Jetson and other edge hardware.

Required Technical Skills:

• 2+ years of experience in Platform Engineering or DevOps/MLOps.
• Strong programming skills are required for automating ML lifecycles and building custom CLI tools for CVengineers.
• Hands-on experience with NVIDIA GPU infrastructure, including managing CUDA libraries and developmentenvironments, GPU Operator, device plugins, and scheduling (MIG, Volcano, or fractional GPU sharing).
• Experience implementing and maintainingMLOpsplatforms such as Kubeflow,MLflow, Weights & Biases (W&B), or DVC for experiment tracking and modelversioning.
• Familiarity with high-performance storage solutions (e.g.,MinIO, WEKA, or Ceph) and data orchestration tools capable of handling terabytes of video/image data.
• Proventrack recordbuilding CI/CD pipelines that include automated model validation, performance benchmarking, and artifact management for both cloud and edge targets.
• Experience with model optimization toolchains, includingTensorRT, ONNX, and quantization techniques, specifically for cross-compilation to ARM targets like NVIDIAJetson.
• Proficiencywith observability stacks (ELK, Prometheus/Grafana) adapted for ML, including monitoring GPU health, training throughput, and model inferencemetrics.
• Strong Linux systems knowledge (Debian/Ubuntu), including networkingfor high-throughput data,storage,and security hardening fordefense-grade productionenvironments.

What We Offer

• Paid Time Off

Allen Control Systems is an Equal Opportunity Employer,providingequal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal,stateor local laws.

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